Course Details
Advanced Python Programming with Flask and API Integration with projects
Data Science
Created On
July 06, 2023Description
Python advanced with projects refers to an approach that combines learning advanced Python concepts with practical project implementation, enabling deeper understanding, problem-solving skills, and real-world experience. Additionally, provide an opportunity to learn how to work with APIs (Application Programming Interfaces), databases, asynchronous programming, multiprocessing, and other advanced topics. They also encourage collaboration, as you may need to work with other developers or contribute to open-source projects.
Overview
Completing the "Advanced Python Programming with Flask and API Integration" course opens up a range of promising prospects for students, as web developers, API integration specialists, data analysts, full stack developers, software engineers, automation engineers, and opportunities in freelancing and entrepreneurship.
Features
- Real-World Projects
- Quizzes
- Assignments
- Downloadable resources
- Completion certificate
- Industry-Relevant Skills
- Career Preparation
What you'll learn
- Python Advanced Concepts
- Object-Oriented Programming (OOP)
- Exception Handling
- Data Manipulation with Pandas and NumPy
- Web Development with Flask
- API Concepts: Web APIs, REST, and SOAP
- Dask: Parallel Computing in Python
- Numpy: Numerical Computing with Numpy
- Introduction to Web API
- Postman: API Testing and Development
Prerequisites
Curriculum
- 17 modules
Programming Language Overview
Installation Python
Introduction : Sublime Text, Visual Studio Code, PyCharm, Anaconda, Atom, Jupyter Notebook, Kite
Virtual Environment
Why Python
Introduction and Comparison
Installation of Anaconda and IDEs
Python Objects and Strings
Container Objects and Mutability
Operators and Precedence
Conditions and Loops
Break, Continue, and Range Function
String Objects Basics
Essential Data Structure in Python
Inbuilt Methods for String Manipulation
Splitting and Joining Strings
String Formatting Functions
Methods for List Manipulation
Lists as Stacks and Queues
List Comprehensions
Dictionary Object Methods
Dictionary Comprehensions
Dictionary View Objects
Basics of Functions and Parameter Passing
Generator Functions
Lambda Functions
Map, Reduce, and Filter Functions
Oops basic concepts.
Creating classes
Pillars of oops
Inheritance
Polymorphism
Encapsulation
Abstraction
Decorator
Class methods and static methods
Special (magic/dunder) methods
Property decorators - getters, setters, and deletes
Handling Exceptions with try-except
Custom Exception Handling
List of Commonly Used Exceptions
Best Practices for Exception Handling
Pandas Series
Pandas DataFrame
Pandas Panel
Basic Functionality of Pandas
Reading Data from Different File Systems
Iteration in Pandas
Sorting in Pandas
Working with Text Data and Customization
Indexing and Selecting in Pandas
Statistical Functions for Data Analysis
Window Functions in Pandas
Date Functionality in Pandas
Time Delta in Pandas
Handling Categorical Data in Pandas
Data Visualization with Pandas
Input/Output Tools in Pandas
Dask Bag
Dask DataFrame
Dask Delayed
Dask Futures
Dask API
Dask Scheduling
Understanding Performance in Dask
Visualizing Task Graphs in Dask
Dask Diagnostics (Local)
Dask Diagnostics (Distributed)
Debugging in Dask
Dask Ordering
Numpy ND Array Object
Numpy Data Types
Numpy Array Attributes
Numpy Array Creation Routines
Numpy Array from Existing Data
Data Array from Numerical Ranges
Numpy Indexing & Slicing
Numpy Advanced Indexing
Numpy Broadcasting
Numpy Iterating over Array
Numpy Array Manipulation
Numpy Binary Operators
Numpy String Functions
Numpy Mathematical Functions
Numpy Arithmetic Operations
Numpy Statistical Functions
Sort, Search & Counting Functions
Numpy Byte Swapping
Numpy Copies & Views
Numpy Matrix Library
Numpy Linear Algebra
Matplotlib
Seaborn
Cufflinks
Plotly
Bokeh
Understanding Web APIs
API vs. Web API: Key Differences
REST and SOAP Architecture
Restful Services: Principles and Implementation
Flask Application Basics
Opening a Link in Flask
Flask Application Routing
URL Building in Flask
HTTP Methods in Flask
Working with Templates in Flask
Flask Project: Food App
Testing APIs with Postman
SQLite
MySQL
MongoDB
Cassandra
Multithreading
Multiprocessing
Weeding script
Image resizing
Jupyter notebook merging, reading etc.
Sending emails
Weather app
Memes generator
Food log app
Web scrapping
Web crawlers for image data sentiment analysis and product review sentiment analysis.
Integration with web portal
Integration with rest api, web portal and mongodb on azure
Deployment on web portal on azure.
Text mining
Social media data churn
Mass copy, paste
Instructors
Skoliko Faculty
₹6500.00
- 17 Modules
- 50 Hours
- Data Science
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